Depth-based defocus map estimation using off-axis apertures

Abstract

This paper presents a depth-based defocus map estimation method from a single camera with multiple off-axis apertures. The proposed estimation algorithm consists of two steps: (i) object distance estimation using off-axis apertures and (ii) defocus map estimation based on the object distance. The proposed method can accurately estimate the defocus map using object distances that are well-characterized in a color shift model-based computational camera. Experimental results show that the proposed method outperforms the state-of-the-art defocus estimation methods in the sense of both accuracy and the estimation range. The proposed defocus map estimation method is suitable for multifocusing, refocusing, and extended depth of field (EDoF) systems.

Depth Camera Using High-Transmittance Off-Axis Dual Electro-Optical Irises

“…The distance between these two sub-cameras is the stereo baseline which determines the farthest distance a depth camera is expected to sense. One alternative to such a stereo camera is using a combination of a single image sensor and off-axis dual irises [10], [15], [16]. A triangular geometry, similar to that between the object and two sub-cameras, can be found with this combination.…”

Segmentation-Based Color Channel Registration for Disparity Estimation of Dual Color-Filtered Aperture Camera

“…Lee et al presented a novel computational imaging system for disparity estimation by inserting a dual color-filtered aperture (DCA) into an ordinary single camera [ 6 ]. The DCA camera generates a pair of color-filtered stereo images in a single shot and then estimates the disparity by registrating the pair of color images [ 7 , 8 ].…”